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The Frontiers of Society, Science and Technology, 2020, 2(11); doi: 10.25236/FSST.2020.021106.

A Mask Detection System Based on Yolov3-Tiny


Guo Cheng1, Shuyang Li2, Yanheng Zhang3, Ran Zhou4

Corresponding Author:
Guo Cheng

1 School of Computing, Sichuan University, Chengdu 610065, China

2 The Henry Samueli School of Engineering, Irvine 92617, the United States

3 School of Mathematics and Information, Fujian Normal University, Fuzhou 350117, China

4 School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu 610000, China


Currently, there is a global outbreak of novel coronavirus pneumonia, which infected many people. One of the most efficient ways to prevent infection is to wear a mask. Thus, mask detection, which essentially belongs to object detection is meaningful for the authorities to prevent and control the epidemic. After comparing different methods utilized in object detection and conducting relevant analysis, YOLO v3-tiny is proved to be suitable for real-time detection.


Object detection, Deep learning, Convolutional neural network, Yolov3-tiny

Cite This Paper

Guo Cheng, Shuyang Li, Yanheng Zhang, Ran Zhou. A Mask Detection System Based on Yolov3-Tiny. The Frontiers of Society, Science and Technology (2020) Vol. 2 Issue 11: 33-41. https://doi.org/10.25236/FSST.2020.021106.


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